Course aims:

Solving concrete practical problems that include elements of data structures and algorithms, programming
Development of programs in a general and / or specific programming language, starting from the specification of the requirements and until the execution, debugging and interpretation of the results
Use of techniques for conceptual modeling of data;
Acquiring knowledge of the types of models and modeling tools used in software application development

Course Entry Requirements:

-database, programming, data annalist

Course contents:

1. Database systems architectures; 2. SQL Advanced. SQL Union, Blind, Injection; 3. Object based database and XML; 4. Unified Modelling Language (UML). Transaction management; 5. Big data analysis; 6. Hadoop architecture and implementation; 7. MapReduce flow design. 8. SQL interaction with MapReduce;

Teaching methods:

lectures, examples, exercises

Learning outcomes:

a) systematic knowledge about the methodologies for making software products b) familiarization with modern concepts and concerns in writing the application software c) knowledge of the types of models and modeling tools used in the development of software applications d) the necessary motivation regarding the importance of the documentation of the soft products, in all the phases of the life cycle

Learning outcomes verification and assessment criteria:

project developing

Recommended reading:

Fowler, M., Scott, K.: UML Distilled, A Brief Guide to the Standard Object Modeling Language, Addison-Wesley, 2nd ed, 2012,
Pressman, R.S, Software Engineering - A Practitioners Approach, McGraw-Hill, 6rd ed, 2009,
-, Agile Modeling Homepage, http://www.agilemodeling.com, -, 2019,
-, Big data overview -Tools and Techniques, Discoveries and Pitfalls, https://web.stanford.edu/class/cs102/lecturenotes/Overview102.pdf, 2019,